content: /* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
  
  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
  You may obtain a copy of the License at
  
      http://www.apache.org/licenses/LICENSE-2.0
  
  Unless required by applicable law or agreed to in writing, software
  distributed under the License is distributed on an "AS IS" BASIS,
  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  See the License for the specific language governing permissions and
  limitations under the License.
  ==============================================================================*/
  
  package org.tensorflow.lite;
  
  import static com.google.common.truth.Truth.assertThat;
  import static org.junit.Assert.fail;
  
  import java.nio.Buffer;
  import java.nio.ByteBuffer;
  import java.nio.ByteOrder;
  import java.nio.FloatBuffer;
  import java.nio.IntBuffer;
  import java.nio.LongBuffer;
  import java.util.HashMap;
  import java.util.Map;
  import org.junit.After;
  import org.junit.Before;
  import org.junit.Test;
  import org.junit.runner.RunWith;
  import org.junit.runners.JUnit4;
  import org.tensorflow.lite.Tensor.QuantizationParams;
  
  /** Unit tests for {@link org.tensorflow.lite.Tensor}. */
  @RunWith(JUnit4.class)
  public final class TensorTest {
  
    private static final String MODEL_PATH =
        "tensorflow/lite/java/src/testdata/add.bin";
  
    private static final String INT_MODEL_PATH =
        "tensorflow/lite/java/src/testdata/int32.bin";
  
    private static final String LONG_MODEL_PATH =
        "tensorflow/lite/java/src/testdata/int64.bin";
  
    private static final String QUANTIZED_MODEL_PATH =
        "tensorflow/lite/java/src/testdata/quantized.bin";
  
    private NativeInterpreterWrapper wrapper;
    private Tensor tensor;
  
    @Before
    public void setUp() {
      wrapper = new NativeInterpreterWrapper(MODEL_PATH);
      float[] oneD = {1.23f, 6.54f, 7.81f};
      float[][] twoD = {oneD, oneD, oneD, oneD, oneD, oneD, oneD, oneD};
      float[][][] threeD = {twoD, twoD, twoD, twoD, twoD, twoD, twoD, twoD};
      float[][][][] fourD = {threeD, threeD};
      Object[] inputs = {fourD};
      Map<Integer, Object> outputs = new HashMap<>();
      outputs.put(0, new float[2][8][8][3]);
      wrapper.run(inputs, outputs);
      tensor = wrapper.getOutputTensor(0);
      assertThat(tensor.index()).isGreaterThan(-1);
    }
  
    @After
    public void tearDown() {
      wrapper.close();
    }
  
    @Test
    public void testBasic() throws Exception {
      assertThat(tensor).isNotNull();
      int[] expectedShape = {2, 8, 8, 3};
      assertThat(tensor.shape()).isEqualTo(expectedShape);
      assertThat(tensor.shapeSignature()).isEqualTo(expectedShape);
      assertThat(tensor.dataType()).isEqualTo(DataType.FLOAT32);
      assertThat(tensor.numBytes()).isEqualTo(2 * 8 * 8 * 3 * 4);
      assertThat(tensor.numElements()).isEqualTo(2 * 8 * 8 * 3);
      assertThat(tensor.numDimensions()).isEqualTo(4);
      assertThat(tensor.name()).isEqualTo("output");
    }
  
    @Test
    public void testCopyTo() {
      float[][][][] parsedOutputs = new float[2][8][8][3];
      tensor.copyTo(parsedOutputs);
      float[] outputOneD = parsedOutputs[0][0][0];
      float[] expected = {3.69f, 19.62f, 23.43f};
      assertThat(outputOneD).usingTolerance(0.1f).containsExactly(expected).inOrder();
    }
  
    @Test
    public void testCopyToNull() {
      try {
        tensor.copyTo(null);
        fail();
      } catch (IllegalArgumentException e) {
        // Success.
      }
    }
  
    @Test
    public void testCopyToByteBuffer() {
      ByteBuffer parsedOutput =
          ByteBuffer.allocateDirect(2 * 8 * 8 * 3 * 4).order(ByteOrder.nativeOrder());
      tensor.copyTo(parsedOutput);
      assertThat(parsedOutput.position()).isEqualTo(2 * 8 * 8 * 3 * 4);
      float[] outputOneD = {
        parsedOutput.getFloat(0), parsedOutput.getFloat(4), parsedOutput.getFloat(8)
      };
      float[] expected = {3.69f, 19.62f, 23.43f};
      assertThat(outputOneD).usingTolerance(0.1f).containsExactly(expected).inOrder();
    }
  
    @Test
    public void testCopyToByteBufferAsFloatBuffer() {
      FloatBuffer parsedOutput =
          ByteBuffer.allocateDirect(2 * 8 * 8 * 3 * 4).order(ByteOrder.nativeOrder()).asFloatBuffer();
      tensor.copyTo(parsedOutput);
      assertThat(parsedOutput.position()).isEqualTo(2 * 8 * 8 * 3);
      float[] outputOneD = {parsedOutput.get(0), parsedOutput.get(1), parsedOutput.get(2)};
      float[] expected = {3.69f, 19.62f, 23.43f};
      assertThat(outputOneD).usingTolerance(0.1f).containsExactly(expected).inOrder();
    }
  
    @Test
    public void testCopyToFloatBuffer() {
      FloatBuffer parsedOutput = FloatBuffer.allocate(2 * 8 * 8 * 3);
      tensor.copyTo(parsedOutput);
      assertThat(parsedOutput.position()).isEqualTo(2 * 8 * 8 * 3);
      float[] outputOneD = {parsedOutput.get(0), parsedOutput.get(1), parsedOutput.get(2)};
      float[] expected = {3.69f, 19.62f, 23.43f};
      assertThat(outputOneD).usingTolerance(0.1f).containsExactly(expected).inOrder();
    }
  
    @Test
    public void testCopyToIntBuffer() {
      wrapper = new NativeInterpreterWrapper(INT_MODEL_PATH);
      tensor = wrapper.getOutputTensor(0);
      IntBuffer parsedOutput = IntBuffer.allocate(1 * 4 * 4 * 12);
      tensor.copyTo(parsedOutput);
      assertThat(parsedOutput.position()).isEqualTo(1 * 4 * 4 * 12);
    }
  
    @Test
    public void testCopyToLongBuffer() {
      wrapper = new NativeInterpreterWrapper(LONG_MODEL_PATH);
      tensor = wrapper.getOutputTensor(0);
      LongBuffer parsedOutput = LongBuffer.allocate(1 * 4 * 4 * 12);
      tensor.copyTo(parsedOutput);
      assertThat(parsedOutput.position()).isEqualTo(1 * 4 * 4 * 12);
    }
  
    @Test
    public void testCopyToInvalidByteBuffer() {
      ByteBuffer parsedOutput = ByteBuffer.allocateDirect(3 * 4).order(ByteOrder.nativeOrder());
      try {
        tensor.copyTo(parsedOutput);
        fail();
      } catch (IllegalArgumentException e) {
        // Expected.
      }
    }
  
    @Test
    public void testCopyToInvalidTypedBuffer() {
      IntBuffer parsedOutput = IntBuffer.allocate(2 * 8 * 8 * 3);
      try {
        tensor.copyTo(parsedOutput);
        fail();
      } catch (IllegalArgumentException e) {
        // Expected.
      }
    }
  
    @Test
    public void testCopyToWrongType() {
      int[][][][] parsedOutputs = new int[2][8][8][3];
      try {
        tensor.copyTo(parsedOutputs);
        fail();
      } catch (IllegalArgumentException e) {
        assertThat(e)
            .hasMessageThat()
            .contains(
                "Cannot convert between a TensorFlowLite tensor with type FLOAT32 and a Java object "
                    + "of type [[[[I (which is compatible with the TensorFlowLite type INT32)");
      }
    }
  
    @Test
    public void testCopyToWrongShape() {
      float[][][][] parsedOutputs = new float[1][8][8][3];
      try {
        tensor.copyTo(parsedOutputs);
        fail();
      } catch (IllegalArgumentException e) {
        assertThat(e)
            .hasMessageThat()
            .contains(
                "Cannot copy between a TensorFlowLite tensor with shape [2, 8, 8, 3] "
                    + "and a Java object with shape [1, 8, 8, 3].");
      }
    }
  
    @Test
    public void testSetTo() {
      float[][][][] input = new float[2][8][8][3];
      float[][][][] output = new float[2][8][8][3];
  
      // Assign from array.
      input[0][0][0][0] = 2.0f;
      tensor.setTo(input);
      tensor.copyTo(output);
      assertThat(output[0][0][0][0]).isEqualTo(2.0f);
  
      // Assign from direct ByteBuffer.
      ByteBuffer inputByteBuffer =
          ByteBuffer.allocateDirect(2 * 8 * 8 * 3 * 4).order(ByteOrder.nativeOrder());
      inputByteBuffer.putFloat(0, 3.0f);
      tensor.setTo(inputByteBuffer);
      tensor.copyTo(output);
      assertThat(output[0][0][0][0]).isEqualTo(3.0f);
  
      // Assign from FloatBuffer view of ByteBuffer.
      inputByteBuffer.rewind();
      FloatBuffer inputFloatBuffer = inputByteBuffer.asFloatBuffer();
      inputFloatBuffer.put(0, 5.0f);
      tensor.setTo(inputFloatBuffer);
      tensor.copyTo(output);
      assertThat(output[0][0][0][0]).isEqualTo(5.0f);
  
      // Assign from (non-direct) FloatBuffer.
      inputFloatBuffer = FloatBuffer.allocate(2 * 8 * 8 * 3);
      inputFloatBuffer.put(0, 5.0f);
      inputFloatBuffer.rewind();
      tensor.setTo(inputFloatBuffer);
      tensor.copyTo(output);
      assertThat(output[0][0][0][0]).isEqualTo(5.0f);
  
      // Assign from scalar float.
      wrapper.resizeInput(0, new int[0]);
      wrapper.allocateTensors();
      float scalar = 5.0f;
      tensor.setTo(scalar);
      FloatBuffer outputScalar = FloatBuffer.allocate(1);
      tensor.copyTo(outputScalar);
      assertThat(outputScalar.get(0)).isEqualTo(5.0f);
  
      // Assign from boxed scalar Float.
      Float boxedScalar = 9.0f;
      tensor.setTo(boxedScalar);
      outputScalar = FloatBuffer.allocate(1);
      tensor.copyTo(outputScalar);
      assertThat(outputScalar.get(0)).isEqualTo(9.0f);
    }
  
    @Test
    public void testSetToInt() {
      wrapper = new NativeInterpreterWrapper(INT_MODEL_PATH);
      tensor = wrapper.getOutputTensor(0);
  
      int[][][][] input = new int[1][4][4][12];
      int[][][][] output = new int[1][4][4][12];
  
      // Assign from array.
      input[0][0][0][0] = 2;
      tensor.setTo(input);
      tensor.copyTo(output);
      assertThat(output[0][0][0][0]).isEqualTo(2);
  
      // Assign from direct ByteBuffer.
      ByteBuffer inputByteBuffer =
          ByteBuffer.allocateDirect(1 * 4 * 4 * 12 * 4).order(ByteOrder.nativeOrder());
      inputByteBuffer.putInt(0, 3);
      tensor.setTo(inputByteBuffer);
      tensor.copyTo(output);
      assertThat(output[0][0][0][0]).isEqualTo(3);
  
      // Assign from IntBuffer view of ByteBuffer.
      inputByteBuffer.rewind();
      IntBuffer inputIntBuffer = inputByteBuffer.asIntBuffer();
      inputIntBuffer.put(0, 5);
      tensor.setTo(inputIntBuffer);
      tensor.copyTo(output);
      assertThat(output[0][0][0][0]).isEqualTo(5);
  
      // Assign from (non-direct) IntBuffer.
      inputIntBuffer = IntBuffer.allocate(1 * 4 * 4 * 12);
      inputIntBuffer.put(0, 5);
      tensor.setTo(inputIntBuffer);
      tensor.copyTo(output);
      assertThat(output[0][0][0][0]).isEqualTo(5);
    }
  
    @Test
    public void testSetToLong() {
      wrapper = new NativeInterpreterWrapper(LONG_MODEL_PATH);
      tensor = wrapper.getOutputTensor(0);
  
      long[][][][] input = new long[1][4][4][12];
      long[][][][] output = new long[1][4][4][12];
  
      // Assign from array.
      input[0][0][0][0] = 2;
      tensor.setTo(input);
      tensor.copyTo(output);
      assertThat(output[0][0][0][0]).isEqualTo(2);
  
      // Assign from direct ByteBuffer.
      ByteBuffer inputByteBuffer =
          ByteBuffer.allocateDirect(1 * 4 * 4 * 12 * 8).order(ByteOrder.nativeOrder());
      inputByteBuffer.putLong(0, 3);
      tensor.setTo(inputByteBuffer);
      tensor.copyTo(output);
      assertThat(output[0][0][0][0]).isEqualTo(3);
  
      // Assign from LongBuffer view of ByteBuffer.
      inputByteBuffer.rewind();
      LongBuffer inputLongBuffer = inputByteBuffer.asLongBuffer();
      inputLongBuffer.put(0, 5);
      tensor.setTo(inputLongBuffer);
      tensor.copyTo(output);
      assertThat(output[0][0][0][0]).isEqualTo(5);
  
      // Assign from (non-direct) LongBuffer.
      inputLongBuffer = LongBuffer.allocate(1 * 4 * 4 * 12);
      inputLongBuffer.put(0, 5);
      tensor.setTo(inputLongBuffer);
      tensor.copyTo(output);
      assertThat(output[0][0][0][0]).isEqualTo(5);
    }
  
    @Test
    public void testSetToNull() {
      try {
        tensor.setTo(null);
        fail();
      } catch (IllegalArgumentException e) {
        // Success.
      }
    }
  
    @Test
    public void testSetToFloatBuffer() {
      float[] input = new float[2 * 8 * 8 * 3];
      float[] output = new float[2 * 8 * 8 * 3];
      FloatBuffer inputFloatBuffer = FloatBuffer.wrap(input);
      FloatBuffer outputFloatBuffer = FloatBuffer.wrap(output);
  
      input[0] = 2.0f;
      input[2 * 8 * 8 * 3 - 1] = 7.0f;
      tensor.setTo(inputFloatBuffer);
      tensor.copyTo(outputFloatBuffer);
      assertThat(output[0]).isEqualTo(2.0f);
      assertThat(output[2 * 8 * 8 * 3 - 1]).isEqualTo(7.0f);
    }
  
    @Test
    public void testSetToInvalidBuffer() {
      Buffer[] inputs = {
        ByteBuffer.allocateDirect(3 * 4).order(ByteOrder.nativeOrder()),
        FloatBuffer.allocate(3),
        IntBuffer.allocate(3),
        LongBuffer.allocate(3)
      };
      for (Buffer input : inputs) {
        try {
          tensor.setTo(input);
          fail();
        } catch (IllegalArgumentException e) {
          // Success.
        }
      }
    }
  
    @Test
    public void testGetInputShapeIfDifferent() {
      ByteBuffer bytBufferInput = ByteBuffer.allocateDirect(3 * 4).order(ByteOrder.nativeOrder());
      assertThat(tensor.getInputShapeIfDifferent(bytBufferInput)).isNull();
  
      float[][][][] sameShapeInput = new float[2][8][8][3];
      assertThat(tensor.getInputShapeIfDifferent(sameShapeInput)).isNull();
  
      float[][][][] differentShapeInput = new float[1][8][8][3];
      assertThat(tensor.getInputShapeIfDifferent(differentShapeInput))
          .isEqualTo(new int[] {1, 8, 8, 3});
  
      Float differentShapeInputScalar = 5.0f;
      assertThat(tensor.getInputShapeIfDifferent(differentShapeInputScalar)).isEqualTo(new int[] {});
    }
  
    @Test
    public void testDataTypeOf() {
      float[] testEmptyArray = {};
      DataType dataType = Tensor.dataTypeOf(testEmptyArray);
      assertThat(dataType).isEqualTo(DataType.FLOAT32);
      float[] testFloatArray = {0.783f, 0.251f};
      dataType = Tensor.dataTypeOf(testFloatArray);
      assertThat(dataType).isEqualTo(DataType.FLOAT32);
      float[][] testMultiDimArray = {testFloatArray, testFloatArray, testFloatArray};
      dataType = Tensor.dataTypeOf(testMultiDimArray);
      assertThat(dataType).isEqualTo(DataType.FLOAT32);
      FloatBuffer testFloatBuffer = FloatBuffer.allocate(1);
      dataType = Tensor.dataTypeOf(testFloatBuffer);
      assertThat(dataType).isEqualTo(DataType.FLOAT32);
      float testFloat = 1.0f;
      dataType = Tensor.dataTypeOf(testFloat);
      assertThat(dataType).isEqualTo(DataType.FLOAT32);
      try {
        double[] testDoubleArray = {0.783, 0.251};
        Tensor.dataTypeOf(testDoubleArray);
        fail();
      } catch (IllegalArgumentException e) {
        assertThat(e).hasMessageThat().contains("cannot resolve DataType of");
      }
      try {
        Float[] testBoxedArray = {0.783f, 0.251f};
        Tensor.dataTypeOf(testBoxedArray);
        fail();
      } catch (IllegalArgumentException e) {
        assertThat(e).hasMessageThat().contains("cannot resolve DataType of [Ljava.lang.Float;");
      }
    }
  
    @Test
    public void testNumDimensions() {
      int scalar = 1;
      assertThat(Tensor.computeNumDimensions(scalar)).isEqualTo(0);
      int[][] array = {{2, 4}, {1, 9}};
      assertThat(Tensor.computeNumDimensions(array)).isEqualTo(2);
      try {
        int[] emptyArray = {};
        Tensor.computeNumDimensions(emptyArray);
        fail();
      } catch (IllegalArgumentException e) {
        assertThat(e).hasMessageThat().contains("Array lengths cannot be 0.");
      }
    }
  
    @Test
    public void testNumElements() {
      int[] scalarShape = {};
      assertThat(Tensor.computeNumElements(scalarShape)).isEqualTo(1);
      int[] vectorShape = {3};
      assertThat(Tensor.computeNumElements(vectorShape)).isEqualTo(3);
      int[] matrixShape = {3, 4};
      assertThat(Tensor.computeNumElements(matrixShape)).isEqualTo(12);
      int[] degenerateShape = {3, 4, 0};
      assertThat(Tensor.computeNumElements(degenerateShape)).isEqualTo(0);
    }
  
    @Test
    public void testFillShape() {
      int[][][] array = {{{23}, {14}, {87}}, {{12}, {42}, {31}}};
      int num = Tensor.computeNumDimensions(array);
      int[] shape = new int[num];
      Tensor.fillShape(array, 0, shape);
      assertThat(num).isEqualTo(3);
      assertThat(shape[0]).isEqualTo(2);
      assertThat(shape[1]).isEqualTo(3);
      assertThat(shape[2]).isEqualTo(1);
    }
  
    @Test
    public void testCopyToScalarUnsupported() {
      wrapper.resizeInput(0, new int[0]);
      wrapper.allocateTensors();
      tensor.setTo(5.0f);
      Float outputScalar = 7.0f;
      try {
        tensor.copyTo(outputScalar);
        fail();
      } catch (IllegalArgumentException e) {
        // Expected failure.
      }
    }
  
    @Test
    public void testUseAfterClose() {
      tensor.close();
      try {
        tensor.numBytes();
        fail();
      } catch (IllegalArgumentException e) {
        // Expected failure.
      }
    }
  
    @Test
    public void testQuantizationParameters_floatModel() {
      QuantizationParams quantizationParams = tensor.quantizationParams();
      float scale = quantizationParams.getScale();
      long zeroPoint = quantizationParams.getZeroPoint();
  
      assertThat(scale).isWithin(1e-6f).of(0.0f);
      assertThat(zeroPoint).isEqualTo(0);
    }
  
    @Test
    public void testQuantizationParameters_quantizedModel() {
      wrapper = new NativeInterpreterWrapper(QUANTIZED_MODEL_PATH);
      tensor = wrapper.getOutputTensor(0);
  
      QuantizationParams quantizationParams = tensor.quantizationParams();
      float scale = quantizationParams.getScale();
      long zeroPoint = quantizationParams.getZeroPoint();
  
      assertThat(scale).isWithin(1e-6f).of(0.25f);
      assertThat(zeroPoint).isEqualTo(127);
    }
  }
  